[1]ZHANG Wei,GE Quanbo,LIU Huaping,et al.AGV active landform exploration and perception in an unknown outdoor environment[J].CAAI Transactions on Intelligent Systems,2021,16(1):152-161.[doi:10.11992/tis.202007025]
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AGV active landform exploration and perception in an unknown outdoor environment
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
16
Number of periods:
2021 1
Page number:
152-161
Column:
吴文俊人工智能科学技术奖论坛
Public date:
2021-01-05
- Title:
- AGV active landform exploration and perception in an unknown outdoor environment
- Keywords:
- mobile robot; movement methods; bayesian framework; active perception; passive perception; geomorphic recognition; vibration data; outdoor geomorphology
- CLC:
- TP391
- DOI:
- 10.11992/tis.202007025
- Abstract:
- The recognition of a complex landform environment by an intelligent robot has been the frontier problem of research in the field of robotics applications. The motion modes adopted by mobile robots differ between landforms, so the selected motion mode is crucial for quickly and accurately identifying the type of landform. To solve this problem, an active perception exploration method is proposed in this paper based on a Bayesian framework. It enables mobile robots to actively explore interesting motion modes and recognize the matching relationship between landform and movement. It can optimize the fuzzy uncertainty in landform recognition. To further verify the reliability of the experiment, we also use a passive recognition strategy to compare and analyze the differences between different strategies. The experimental results show that the active perception method can plan effective landform recognition action sequences and guide mobile robots to actively perceive the target landform. The landform recognition effect of active perception is better than that of passive perception in an unknown outdoor environment.
- References:
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Last Update:
2021-02-25